As voice communication such as hands-free voice communication, and communication over wireless devices such as headsets becomes more ubiquitous the need for acoustic echo removal is becoming increasingly important. A typical hands free voice communication system includes one or more microphones and one or more loudspeakers. Additional components include an amplifier and an analog-to-digital converter (ADC) to generate an input signal. One or more output signals that drive the loudspeaker(s) are converted to analog form to drive the loudspeakers. Echoes may be caused by feedback from the loudspeaker(s) to the microphone(s), so that the microphone(s) pick up both a desired signal, e.g., voice of a local talker, and the sound from the loudspeaker(s), e.g., voice of a remote talker being output from the loudspeaker(s), that is, the output signal.
A traditional echo canceller takes a corrupted microphone signal and removes the acoustic echo from the loudspeaker output. In such an echo canceller, the feedback path is assumed to be a linear time invariant system that can be modeled with in impulse response. That impulse response is estimated with an adaptive linear filter that predicts the echo from an echo reference signal created from the output signal or a signal related thereto. The predicted echo from the adaptive filter is subtracted from the input. The goal of the adaptive filter of a traditional echo canceller is to model the feedback response of the feedback path sufficiently accurately such that the output of the adaptive filter matches the echo component in the microphone signal. One key issue with echo cancellation systems is the sensitivity to errors in the modeling of the feedback system response. If there is error in this model then the cancellation signal may reinforce the echo rather than remove it.
Echo suppression overcomes some of the disadvantages of echo cancellation. A fundamental difference between echo suppression and echo cancellation is that a suppressor does not subtract an estimate of the echo from the microphone signal. Rather the suppressor, in one version, calculates frequency domain suppression gains based on the estimated spectral content due to echo in the input signal, and applies the calculated gains to the input signal to suppress the echo. The echo reference signal is used indirectly to adapt the feedback system model from which the suppression gains are derived. The estimation of spectral content operates on frames of samples and with reasonably wide spectral bands. Hence, there is inherent tolerance for uncertainty in what is used as the reference signal compared to an echo cancelling system.
Significant nonlinear behavior has been observed in many of the audio components commonly used, and such nonlinear behavior can cause error in the modeling. When an echo cancellation method attempt to address nonlinear behavior in the feedback system response, care must be taken to ensure the nonlinearities are modeled accurately.